Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analyses

Articles published in several prominent educational journals were examined to investigate the use of data-analysis tools by researchers in four research paradigms: between-subjects univariate designs, between-subjects multivariate designs, repeated measures designs, and covariance designs. In addition to examining specific details pertaining to the research design (e.g., sample size, group size equality/inequality) and methods employed for data analysis, we also catalogued whether: (a) validity assumptions were examined, (b) effect size indices were reported, (c) sample sizes were selected based on power considerations, and (d) appropriate textbooks and/or articles were cited to communicate the nature of the analyses that were performed. Our analyses imply that researchers rarely verify that validity assumptions are satisfied and accordingly typically use analyses that are nonrobust to assumption violations. In addition, researchers rarely report effect size statistics, nor do they routinely perform power analyses to determine sample size requirements. We offer many recommendations to rectify these shortcomings.Social Sciences and Humanities Research Counci

High Diversity of the Fungal Community Structure in Naturally-Occurring Ophiocordyceps sinensis

BACKGROUND: Ophiocordyceps sinensis (syn. Cordyceps sinensis), which is a parasite of caterpillars and is endemic to alpine regions on the Tibetan Plateau, is one of the most valuable medicinal fungi in the world. "Natural O. sinensis specimens" harbor various other fungi. Several of these other fungi that have been isolated from natural O. sinensis specimens have similar chemical components and/or pharmaceutical effects as O. sinensis. Nevertheless, the mycobiota of natural O. sinensis specimens has not been investigated in detail. METHODOLOGY/PRINCIPAL FINDINGS: Based on the technique of PCR-single-strand conformation polymorphism (PCR-SSCP), the mycobiota of three different sections (stromata, sclerotia, and mycelial cortices) from natural O. sinensis specimens were investigated using both culture-dependent and -independent methods. For the culture-dependent method, 572 fungal strains were isolated, and 92 putative operational taxonomic units (OTUs) were identified from 226 sequenced strains with the threshold of 97%. For the culture-independent method, 490 fungal clones were identified from about 3000 clones of ITS fragments from the whole-community DNA; based on PCR-SSCP analyses, 266 of these clones were selected to be sequenced, and 118 putative OTUs were detected. The overwhelming majority of isolates/clones and OTUs were detected from mycelial cortices; only a few were detected from stromata and sclerotia. The most common OTUs detected with both methods belonged to Ascomycota; however, only 13 OTUs were detected simultaneously by both methods. Potential novel lineages were detected by each of the two methods. CONCLUSIONS/SIGNIFICANCE: A great number of fungal species present in the mycobiota of naturally-occurring O. sinensis specimens were detected, and many of them may represent undescribed lineages. That only a few of the same OTUs were detected by both methods indicated that different methods should be used. This study increased our understanding about the fungal community structure of this valuable medicinal herb

The effect of skewness and kurtosis on the robustness of linear mixed models

This study analyzes the robustness of the linear mixed model (LMM) with the Kenward–Roger (KR) procedure to violations of normality and sphericity when used in split-plot designs with small sample sizes. Specifically, it explores the independent effect of skewness and kurtosis on KR robustness for the values of skewness and kurtosis coefficients that are most frequently found in psychological and educational research data. To this end, a Monte Carlo simulation study was designed, considering a split-plot design with three levels of the between-subjects grouping factor and four levels of the within-subjects factor. Robustness is assessed in terms of the probability of type I error. The results showed that (1) the robustness of the KR procedure does not differ as a function of the violation or satisfaction of the sphericity assumption when small samples are used; (2) the LMM with KR can be a good option for analyzing total sample sizes of 45 or larger when their distributions are normal, slightly or moderately skewed, and with different degrees of kurtosis violation; (3) the effect of skewness on the robustness of the LMM with KR is greater than the corresponding effect of kurtosis for common values; and (4) when data are not normal and the total sample size is 30, the procedure is not robust. Alternative analyses should be performed when the total sample size is 30